Search results for: generalized autoregressive score model

Authors: Arsalan Hassan Pour, Mansoureh Jeihani, Samira Ahangari

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Distracted driving has been one of the most integral concerns surrounding our daily use of vehicles since the invention of the automobile. While much attention has been recently given to cell phones related distraction, commercial billboards along roads are also candidates for drivers' visual and cognitive distractions, as they may take drivers’ eyes from the road and their minds off the driving task to see, perceive and think about the billboard’s content. Using a driving simulator and a head-mounted eye-tracking system, speed change, acceleration, deceleration, throttle response, collision, lane changing, and offset from the center of the lane data along with gaze fixation duration and frequency data were collected in this study. Some 92 participants from a fairly diverse sociodemographic background drove on a simulated freeway in Baltimore, Maryland area and were exposed to three different billboards to investigate the effects of billboards on drivers’ behavior. Participants glanced at the billboards several times with different frequencies, the maximum of which occurred on the billboard with the highest cognitive load. About 74% of the participants didn’t look at billboards for more than two seconds at each glance except for the billboard with a short visible area. Analysis of variance (ANOVA) was performed to find the variations in driving behavior when they are invisible, readable, and post billboards area. The results show a slight difference in speed, throttle, brake, steering velocity, and lane changing, among different areas. Brake force and deviation from the center of the lane increased in the readable area in comparison with the visible area, and speed increased right after each billboard. The results indicated that billboards have a significant effect on driving performance and visual attention based on their content and visibility status. Generalized linear model (GLM) analysis showed no connection between participants’ age and driving experience with gaze duration. However, the visible distance of the billboard, gender, and billboard content had a significant effect on gaze duration.

Keywords: ANOVA, billboards, distracted driving, drivers' behavior, driving simulator, eye-Tracking system, GLM

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Authors: Mehrdad Rezaei, Reza Haghmaram, Nima Amjadi

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This paper proposes an operating and cost optimization model for micro-grid (MG). This model takes into account emission costs of NOx, SO2, and CO2, together with the operation and maintenance costs. Wind turbines (WT), photovoltaic (PV) arrays, micro turbines (MT), fuel cells (FC), diesel engine generators (DEG) with different capacities are considered in this model. The aim of the optimization is minimizing operation cost according to constraints, supply demand and safety of the system. The proposed genetic algorithm (GA), with the ability to fine-tune its own settings, is used to optimize the micro-grid operation.

Keywords: micro-grid, optimization, genetic algorithm, MG

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Authors: Neta Kela Madar, Tali Teeni-Harari, Tamar Icekson, Yaron Sela

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This paper proposes and empirically tests a theoretical model positing relationships between dispositional optimism, emotional intelligence, and entrepreneurial intention. To author's best knowledge, this study examined for the first time the role of dispositional optimism together with emotional intelligence as predictors of entrepreneurial intentions. The study findings suggest that optimism may increase entrepreneurial intentions indirectly by enhancing emotional intelligence/ model formulation is based on a random survey of students (N= 227). Model parameter estimation was supported by Structural Equation Modeling (SEM). Results indicate that students’ optimism and emotional intelligence are associated with increased levels of entrepreneurial intention. Additionally, the present study argues that emotional intelligence mediates the positive relationship between optimism and entrepreneurial intention. Theoretical and practical implications of this model are discussed.

Keywords: entrepreneurial intentions, emotional intelligence, optimism, dispositional optimism

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Authors: Chaliya Wamaloon, Malee Chaisaena, Nusara Prasertsri

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Informal caregivers providing home-based palliative and end-of-life (EOL) care to people with advanced cancer is needed, however, there has not been develop caregiver skills for the EOL in cancer patients. The aim of this research was to study the model development of caregiver skills for the EOL in cancer patients. Mixed methods research was conducted in 3 phases. All subjects were in Ubon Rathchathani Cancer Hospital including 30 EOL cancer patient caregivers, 30 EOL cancer patients, and 111 health care professionals who provided care for the EOL cancer patients and 30 EOL target participants who had been trained to be cancer patient caregivers. The research tools were questionnaires, semi structured interviews, and caregiver skills questionnaires. Data were analyzed by using percentage, mean, standard deviation, pair t-test, and content analysis. The result from this study showed the model development of caregiver skills for cancer patients consisted of 9 domains skills: 1. monitoring, 2. interpreting, 3. making decisions, 4. taking action, 5. making adjustments, 6. providing hands-on care, 7. accessing resources, 8. working together with the ill patients, and 9. navigating the healthcare system. The model composed of skills development curriculum for cancer patient caregivers, Manual of palliative care for caregivers, diary of health care records for cancer patients, and the evaluation model of development of caregiver skills for EOL cancer patients. The results of the evaluation in the development model of caregiver skills for EOL cancer patients showed that the caregivers were satisfied with the model of development for caregiver skills at a high level. The comparison of the caregiver skills before and after obtaining the development of caregivers skills revealed that it improved at a statistically significant level (p < 0.05).

Keywords: caregiver, caregiver skills, cancer patients, end of life

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Authors: Nur Azaliah Abu Bakar, Harihodin Selamat, Mohd Nazri Kama

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This article provides a systematic review of existing research related to the Service-oriented Enterprise Architecture (SoEA) adoption and maturity measurement model. The review’s main goals are to support research, to facilitate other researcher’s search for relevant studies and to propose areas for future studies within this area. In addition, this article provides useful information on SoEA adoption issues and its related maturity model, based on research-based knowledge. The review results suggest that motives, critical success factors (CSFs), implementation status and benefits are the most frequently studied areas and that each of these areas would benefit from further exposure.

Keywords: systematic literature review, service-oriented architecture, adoption, maturity model

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Authors: Remy Kulagowski, Tobias Sturm, Audrey Leopold, Aurelie Metay, Josephine Peigne, Alexis Thoumazeau, Alain Brauman, Bruno Fogliani, Florent Tivet

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A major challenge for agriculture is to enhance productivity while limiting the impact on the environment. Conservation agriculture (CA) is one strategy whereby both sustainability and productivity can be achieved by preserving and improving the soil quality. Soils provide and regulate a large number of ecosystem services (ES) such as agricultural productivity and climate change adaptation and mitigation. The aim of this study is to assess the impacts of contrasted CA crop management on soil functions for maize (Zea mays L.) cultivation in an eight years field experiment (2010-2018). The study included two CA practices: direct seeding in dead mulch (DM) and living mulch (LM), and conventional plough-based tillage (CT) practices on a fluvisol in New Caledonia (French Archipelago in the South Pacific). In 2018, soil quality of the cropping systems were evaluated with the Biofunctool® set of indicators, that consists in twelve integrative, in-field, and low-tech indicators assessing the biological, physical and chemical properties of soils. Main soil functions were evaluated including (i) carbon transformation, (ii) structure maintenance, and (iii) nutrient cycling in the ten first soil centimeters. The results showed significant higher score for soil structure maintenance (e.g., aggregate stability, water infiltration) and carbon transformation function (e.g., soil respiration, labile carbon) under CA in DM and LM when compared with CT. Score of carbon transformation index was higher in DM compared with LM. However, no significant effect of cropping systems was observed on nutrient cycling (i.e., nitrogen and phosphorus). In conclusion, the aggregated synthetic scores of soil multi-functions evaluated with Biofunctool® demonstrate that CA cropping systems lead to a better soil functioning. Further analysis of the results with agronomic performance of the soil-crop systems would allow to better understand the links between soil functioning and production ES of CA.

Keywords: conservation agriculture, cropping systems, ecosystem services, soil functions

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Authors: Humeyra Bolakar Tosun

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The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

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Authors: M. K. Wijayarathna, S. M. Buddika Harshanath

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Monitoring student engagement has become a crucial part of the educational process and a reliable indicator of the capacity to retain information. As online learning classrooms are now more common these days, students' attention levels have become increasingly important, making it more difficult to check each student's concentration level in an online classroom setting. To profile student attention to various gradients of engagement, a study is a plan to conduct using machine learning models. Using a convolutional neural network, the findings and confidence score of the high accuracy model are obtained. In this research, convolutional neural networks are using to help discover essential emotions that are critical in defining various levels of participation. Students' attention levels were shown to be influenced by emotions such as calm, enjoyment, surprise, and fear. An improved virtual learning system was created as a result of these data, which allowed teachers to focus their support and advise on those students who needed it. Student participation has formed as a crucial component of the learning technique and a consistent predictor of a student's capacity to retain material in the classroom. Convolutional neural networks have a plan to implement the platform. As a preliminary step, a video of the pupil would be taken. In the end, researchers used a convolutional neural network utilizing the Keras toolkit to take pictures of the recordings. Two convolutional neural network methods are planned to use to determine the pupils' attention level. Finally, those predicted student attention level results plan to display on the graphical user interface of the System.

Keywords: HTML5, JavaScript, Python flask framework, AI, graphical user

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Authors: Solopova Olga

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The present paper briefly recalls theoretical preconditions for investigating cognitive-discursive models of future in political discourse. The author reviews theories and methods used for strengthening a future focus in this discourse working out two main tools – a model of future and a metaphorical scenario. The paper examines the implications of metaphorical analogies for modeling future in mass media. It argues that metaphor is not merely a rhetorical ornament in the political discourse of media regulation but a conceptual model that legislates and regulates our understanding of future.

Keywords: cognitive approach, future research, political discourse, model, scenario, metaphor

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Authors: Nurudeen Oluwasola Lasisi

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The COVID-19 is an infection caused by coronavirus, which has been designated as a pandemic in the world. In this paper, we proposed a model to study the effect of distancing and wearing masks on the transmission of COVID-19 infection dynamics. The invariant region of the model is established. The COVID-19 free equilibrium and the reproduction number of the model were obtained. The local and global stability of the model is determined using the linearization technique method and Lyapunov method. It was found that COVID-19 free equilibrium state is locally asymptotically stable in feasible region Ω if R₀ < 1 and globally asymptomatically stable if R₀ < 1, otherwise unstable if R₀ > 1. More so, numerical analysis and simulations of the dynamics of the COVID-19 infection are presented.

Keywords: distancing, reproduction number, wearing of mask, local and global stability, modelling, transmission

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Authors: S. Zamir

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The modern era has brought with it significant organizational changes. These changes have not bypassed the academic world, and along with the old academic bonds that include a world of knowledge and ethics, academic faculty members are required more than ever not only to survive in the academic world, but also to thrive and flourish and position themselves as modern and opinionated academicians. Based upon the writings of organizational consultants, the article suggests a 10 X C model for cultivating an academic backbone, as well as emphasizing its input to the professional growth of university and college academics: Competence, Calculations of pain & gain, Character, Commitment, Communication, Curiosity, Coping, Courage, Collaboration and Celebration.

Keywords: academic career, academicians, higher education, the 10xC model

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Authors: Prashant Neupane, Sumitra Kafle, Asmi Pandey, Laura Mitchell

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Pain following caesarean section can influence recovery, patient satisfaction, breast feeding success and mother-child bonding. Since the introduction of enhanced recovery protocols, mothers are often discharged 24 hours later. We identified concerns within our hospital with mothers tolerating poorly controlled pain in order to achieve earlier discharge and subsequently suffering significant pain at home with inadequate analgesia. Methods: We conducted a prospective audit of analgesic prescribing and post-operative pain scores after caesarean section. Mothers were seen on post-operative day one, their pain score recorded on a verbal analogue score from 0-10, and their prescription chart reviewed. A follow-up phone call was then made on post-operative day 3-7 to enquire about pain scores and analgesia use at home. Following this, a standardized proforma for prescribing after the caesarean section was introduced, including the addition of dihydrocodeine that patients can take home following discharge. There were educational update sessions for anesthetists and midwifes, and then a re-audit was conducted months later. Results: Data was collected from 50 women before and after the introduction of the change. Initial audit showed that there was considerable variation in prescribing, with four women prescribed no regular analgesia at all and inconsistency in the dose of oral morphine prescribed. Women were not given any form of analgesia to take home after discharge and were advised to take regular paracetamol and ibuprofen. However, 31/50 (62%) reported that they needed additional analgesia and eight women (16%) even sought prescription for additional analgesia from elsewhere. After the introduction of the change, prescribing was more consistent with all patients prescribed regular analgesia. 46/50 patients were given dihydrocodeine on discharge. Mean pain scores on post-operative day one improved from 5.16 to 3.9, and at home improved from 6.18 to 2.58. Use of dihydrocodeine at home significantly improved patients reporting of severe pain at home from 24% to zero. Discussion: Lack of strong analgesia out of the hospital and the increased demands on activity levels means that women are frequently in more pain at home after discharge. Introduction of a standardized prescription proforma, including the use of to-take-out dihydrocodeine, was successful in improving patient pain scores and the requirement for additional analgesia, both in hospital and at home.

Keywords: analgesia, caesarean section, post-operative pain, standardised

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Authors: Fernanda Ludmilla Rossi Rocha, Thamiris Cavazzani Vegro, Silvia Helena Henriques Camelo, Carmen Silvia Gabriel, Andrea Bernardes

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Introduction: Organizations are cultural, symbolic and imaginary systems composed by values and norms. These values and norms represent the organizational culture, which determines the behavior of the workers, guides the work practices and impacts the quality of care and the safety culture of health services worldwide. Objective: To analyze the organizational culture of a public and a private hospital in Brazil. Method: Descriptive study with quantitative approach developed in a public and in a private hospital of Brazil. Sample was composed by 281 nursing workers, of which 73 nurses and 208 nursing auxiliaries and technicians. The data collection instrument comprised the Brazilian Instrument for Assessing Organizational Culture. Data were collected from March to December 2013. Results: At the public hospital, the results showed an average score of 2.85 for the values concerning cooperative professionalism (CP); 3.02 for values related to hierarchical rigidity and the centralization of power (HR); 2.23 for individualistic professionalism and competition at work (IP); 2.22 for values related to satisfaction, well-being and motivation of workers (SW); 3.47 for external integration (EI); 2.03 for rewarding and training practices (RT); 2.75 for practices related to the promotion of interpersonal relationships (IR) About the private hospital, the results showed an average score of 3.24 for the CP; 2.83 for HR; 2.69 for IP; 2.71 for SW; 3.73 for EI; 2.56 for RT; 2.83 for IR at the hospital. Discussion: The analysis of organizational values of the studied hospitals shows that workers find the existence of hierarchical rigidity and the centralization of power in the institutions; believed there was cooperation at workplace, though they perceived individualism and competition; believed that values associated with the workers’ well-being, satisfaction and motivation were seldom acknowledged by the hospital; believed in the adoption of strategic planning actions within the institution, but considered interpersonal relationship promotion, continuous education and the rewarding of workers to be little valued by the institution. Conclusion: This work context can lead to professional dissatisfaction, compromising the quality of care and contributing to the occurrence of occupational diseases.

Keywords: nursing management, organizational culture, quality of care, interpersonal relationships

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Authors: Tarek Abdel Azim Ahmed, Eman Sarhan Shaker

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This research aims to explore how well the extended model of internet commerce adoption (eMICA) model is often used to determine the extent of internet commerce adoption in the travel agencies sector in both Egypt and Kingdom of Saudi Arabia (KSA). The web content analysis method was used to analyze the level of adoption of Egyptian travel agencies and Saudi travel agencies according to data immensely available on their websites. Therefore, each site was categorized according to the phases and levels proposed. In order to achieve this, 120 websites were evaluated by the two authors over a three-month period, from August to October 2020, and then categorized according to the phases and levels of (eMICA). The results show that there are deficiencies in the application of the eMICA model by both KSA and Egyptian travel agencies, generally, updating their websites, the absence of quality certification, offering secure online payment, virtual tours, and videos using Flash animation. In general, the Egyptian companies slightly outperformed the KSA ones in applying eMICA model.

Keywords: e-commerce, internet marketing, eMICA, travel agencies, websites

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Authors: Elizabeth Hoyos, Hernán Alvarez, Diana Lopez, Yesid Montoya

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The main goal of this research relates to the modeling of FSW from a different or unusual perspective coming from mechanical engineering, particularly looking for a way to establish process windows by assessing soundness of the joints as a priority and with the added advantage of lower computational time. This paper presents the use of a previously developed model applied to specific aspects of soundness evaluation of AA7075 FSW welds. EMSO software (Environment for Modeling, Simulation, and Optimization) was used for simulation and an adapted CNC machine was used for actual welding. This model based approach showed good agreement with the experimental data, from which it is possible to set a window of operation for commercial aluminum alloy AA7075, all with low computational costs and employing simple quality indicators that can be used by non-specialized users in process modeling.

Keywords: aluminum AA7075, friction stir welding, phenomenological based semiphysical model, processing map

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Authors: Erim Koyun

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This paper aim to construct a mathematical model for Underwater vehicles under load variation test conditions. Propeller effects on underwater vehicle are investigated. Body with counter rotating propeller model is analyzed by CFD methods, thus forces and moment are obtained. Propeller effects of vehicle’s hydrodynamic performance under load variation conditions will be investigated. Additionally, pressure contour is examined for differences between different load conditions. Axial force equation is established using hydrodynamic coefficients, which contains resistance, thrust, and additional coefficients occurs due to load variations. Additional coefficients helps to express completely axial force on underwater vehicle. When the vehicle accelerates, additional force occurs besides thrust force increment. This is propeller effect on the body. Hence, mathematical model cover this effect. For CFD analysis, the incompressible, three-dimensional, and unsteady Reynolds Averaged Navier-Stokes equations will be used Numerical results is verified with experimental results for verification. The overall goal of this study is to present complementary mathematical model for body with counter rotating propeller.

Keywords: counter rotating propeller, CFD, hydrodynamic mathematic model, hydrodynamics analysis, thrust deduction

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Authors: Amina Akhtar, Rory O'Connor

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Introduction: There remains significant morbidity and mortality in young pedestrians hit by motor vehicles, even in the era of pedestrian crossings and speed limits. The aim of this study was to compare incidence and injury severity of motor vehicle-related pedestrian trauma according to time of day and season in a young population, based on the supposition that injuries would be more prevalent during dusk and dawn and during autumn and winter. Methods: Data was retrieved for patients between 10-25 years old from the National Trauma Audit and Research Network (TARN) database who had been involved as pedestrians in motor vehicle accidents between 2015-2020. The incidence of injuries, their severity (using the Injury Severity Score [ISS]), hospital transfer time, and mortality were analysed according to the hours of daylight, darkness, and season. Results: The study identified a seasonal pattern, showing that autumn was the predominant season and led to 34.9% of injuries, with a further 25.4% in winter in comparison to spring and summer, with 21.4% and 18.3% of injuries, respectively. However, visibility alone was not a sufficient factor as 49.5% of injuries occurred during the time of darkness, while 50.5% occurred during daylight. Importantly, the greatest injury rate (number of injuries/hour) occurred between 1500-1630, correlating to school pick-up times. A further significant relationship between injury severity score (ISS) and daylight was demonstrated (p-value= 0.0124), with moderate injuries (ISS 9-14) occurring most commonly during the day (72.7%) and more severe injuries (ISS>15) occurred during the night (55.8%). Conclusion: We have identified a relationship between time of day and the frequency and severity of pedestrian trauma in young people. In addition, particular time groupings correspond to the greatest injury rate, suggesting that reduced visibility coupled with school pick-up times may play a significant role. This could be addressed through a targeted public health approach to implementing change. We recommend targeted public health measures to improve road safety that focus on these times and that increase the visibility of children combined with education for drivers.

Keywords: major trauma, paediatric trauma, road traffic accidents, diurnal pattern

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Authors: Sreelekha Prakash, Yulong Gu

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Background: About 61% of adults surveyed across 25 states reported they had experienced at least one type of Adverse Childhood Experience (ACE) before 18 years of age. Relationships between ACEs and a variety of substance-related behaviors and behavioral health have been reported in previous studies. ACEs can have lasting, negative effects on health, well-being, as well as life opportunities such as education and job potential. Objectives: For the current research, the aim was to assess the factors affecting substance use behavior in young adults. The further onset of drug use and its association was analyzed with ACEs and mental health. Method: The young adults from a county in the north-eastern United States were invited to participate in an online questionnaire survey with prior consent through an IRB approved study. The Survey included questions related to social determinants of health, 10 item ACE questionnaire, and substance use related to Alcohol, Marijuana, Opioids, Stimulants, and other drugs. PHQ-9 questionnaire was used to assess cognitive health. Results: Data was analyzed for the 244 completed surveys {68% (165) were females, and 78% (190) were Whites}. The average age of the participants was 26.7 years, and approximately 80% were lifelong residents of the county or year-round residents. Of the respondents, 50% (122) were high school graduates with some college education, and 56% (136) had a full-time jobs. Past 30-day usage for alcohol was 76% (72), and marijuana was 28.4% (27). The data showed that the higher the ACE scores, the younger they start using any substance (p < 0.0001). The data for PHQ-9 and ACE scores showed that the higher the ACE score, the higher the PHQ-9 score, with a significant p-value (p 0.0001). The current data also showed a significant association with other drugs; marijuana use showed significance for 30 days of use (p 0.0001), stimulant use (0.0008), prescription drug misuse (0.01), and opioids (0.01). Conclusion: These findings further support the association between ACEs and initiation of drug use and its correlation with mental health symptoms. Promoting a safe and supportive environment for children and youth in their earlier ages can prevent the youth and young adults from the effects of drug use and create healthy living habits for young adults.

Keywords: subtance use, young adults, adverse childhood experience, PHQ-9

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Authors: Çağla Aras, Kübra Bi̇nay, Aysberg Şamil önlü, Mine Baydan Aran, Dicle Aras

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The purpose of the present research was to investigate the acute effects of 30-min hatha yoga and 30-min resistance-based aerobic exercise (RBAE) on computerized dynamic posturography (CDP) and functional head impulse test (fHIT) scores in adult female yoga practitioners. To reach this aim, ten participants executed CDP and fHIT three times in total: at rest, after yoga, and after RBAE. The yoga practice lasted a total of 30 minutes, including 25 min of asanas and 5 minutes of savasana. RBAE lasted a total of 30 minutes with an intensity of 70-75% of the heart rate reserve method. When the results were examined, no change was observed in any parameters of the fHIT scores due to resting or exercise implementation. On the contrary, some changes were observed in CDP test results depending on the type of exercise. The post-RBAE somatosensory and visual systems values were higher than resting (p<0.05). The composite balance score derived after RBAE was found to be improved when compared to post-yoga and resting values (p<0.01). Lastly, the post-RBAE vestibular system score was found to be statistically significantly higher than the post-Yoga values. In addition, it was observed that body composition parameters, especially decreasing BW, LBM, PBF, MBF and TBW, were associated with improved postural stability values. According to the results, it can be stated that neither hatha yoga nor resistance-based aerobic exercise has an acute effect on functional vestibulo-ocular reflex. In addition, although there was no change in balance level after yoga, it was observed that RBAE performed at 70-75% of the heart rate reserve and for 30 minutes had positive acute effects on postural stability and balance.

Keywords: hatha yoga, resistance training, aerobic training, high intensity training, computerized dynamic posturography, functional head impulse test

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Onyeke Paul Chuks

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Nigeria is ranked among the developing nations and a country with a low income per capita. The consequences of this economic situation have led to the low achievement records below UN benchmark especially in the area of basic education for her citizens. The country is, however, making relentless efforts at arresting the situation by making budgetary allocations to ensure the realization of Millennium Development Goal No. 2 which is achieving universal basic education, her distressed economy notwithstanding. Basic education which comprises primary and lower secondary education as well as pre-primary and/or adult literacy programs have suffered serious setbacks orchestrated by the dwindling of the nation’s economy. This category of education being the bedrock of all other levels of education is regarded as a priority by developing countries and also the focus of the Education for All Movement led by UNESCO. The introduction of child-friendly school model is one of the strategies designed by UNESCO to achieving this all important MDGs goal No. 2. Child-friendly education model is aimed at replacing the out-dated, mundane, regimented and officious school administrative model where the basic rights of school children are trampled upon with impunity and community participation in school activities is viewed as unnecessary interference by school managers. This paper ex-rayed the potential obstacles likely to impinge on the implementation of child-friendly school model in Nigeria especially from the angle of her distressed economy and the colossal effects of the corrupt practices bedeviling the nation. The paper as well outlines prospects for the successful implementation of the child-friendly school model in Nigeria.

Keywords: child-friendly school, distressed economy, model, Nigeria

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: H. Baltache, M. El Amine. Monir, R. Khenata, D. Rached, T. Seddik

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The first principles calculations based on the density functional theory (DFT) by using the full-potential linearized augmented plane wave (FP-LAPW) method within the generalized gradient approximation (GGA) in order to investigate the structural and electronic properties of Cd1-xVxS alloy at x = 0.25 in zincblende structure. For the structural properties, we have calculated the equilibrium lattice parameters, such as lattice constant, bulk modulus and first pressure derivatives of the bulk modulus. From the electronic structure, we obtain that Cd0.75V0.25S alloy is nearly half-metallic. The analysis of the density of states (DOS) curves allow to evaluate the spin-exchange splitting energies Δx(d) and Δx(pd) that are generated by V-3d states, where the effective potential for spin-down case is attractive than for spin-up case. Calculations of the exchange constants N0α (valence band) and N0β (conduction band) are served to describe the magnetic behavior of the compounds.

Keywords: first-principles calculations, structural properties, electronic properties

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Authors: Theddeus T. Akano, Omotayo A. Fakinlede

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The modelling of physical phenomena, such as the earth’s free oscillations, the vibration of strings, the interaction of atomic particles, or the steady state flow in a bar give rise to Sturm-Liouville (SL) eigenvalue problems. The boundary applications of some systems like the convection-diffusion equation, electromagnetic and heat transfer problems requires the combination of Dirichlet and Neumann boundary conditions. Hence, the incorporation of Robin boundary condition in the analyses of Sturm-Liouville problem. This paper deals with the computation of the eigenvalues and eigenfunction of generalized Sturm-Liouville problems with Robin boundary condition using the finite element method. Numerical solutions of classical Sturm–Liouville problems are presented. The results show an agreement with the exact solution. High results precision is achieved with higher number of elements.

Keywords: Sturm-Liouville problem, Robin boundary condition, finite element method, eigenvalue problems

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Authors: Julio Jesus Salazar, Max Jesus De Lama

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The challenges of water management are aggravated by global change, which implies high complexity and associated uncertainty; water management is difficult because water networks cross domains (natural, societal, and political), scales (space, time, jurisdictional, institutional, knowledge, etc.) and levels (area: patches to global; knowledge: a specific case to generalized principles). In this context, we need to apply natural and non-natural measures to manage water and soil. The Basin Management Methodology considers multifunctional measures of natural water retention and erosion control and soil formation to protect water resources and address the challenges related to the recovery or conservation of the ecosystem, as well as natural characteristics of water bodies, to improve the quantitative status of water bodies and reduce vulnerability to floods and droughts. This method of water management focuses on the positive impacts of the chemical and ecological status of water bodies, restoration of the functioning of the ecosystem and its natural services; thus, contributing to both adaptation and mitigation of climate change. This methodology was applied in 7 interventions in the sub-basin of the Shullcas River in Huancayo-Junín-Peru, obtaining great benefits in the framework of the participation of alliances of actors and integrated planning scenarios. To implement the methodology in the sub-basin of the Shullcas River, a process called Climate Smart Territories (CST) was used; with which the variables were characterized in a highly complex space. The diagnosis was then worked using risk management and adaptation to climate change. Finally, it was concluded with the selection of alternatives and projects of this type. Therefore, the CST approach and process face the challenges of climate change through integrated, systematic, interdisciplinary and collective responses at different scales that fit the needs of ecosystems and their services that are vital to human well-being. This methodology is now replicated at the level of the Mantaro river basin, improving with other initiatives that lead to the model of a resilient basin.

Keywords: climate-smart territories, climate change, ecosystem services, natural measures, Climate Smart Territories (CST) approach

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Authors: Deycy Janeth Sanchez Preciado, Bjorn Claes, Paola Andrade

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The development of appropriate environmentally friendly technologies has aided communities in rural areas in emerging economies to better use their natural resources, increase productivity while reducing pollution. Moreover, it has improved their innovation capabilities and ability to develop products for new markets. However, despite the advances, the adoption of these technologies is not generalized and does not always show the expected benefits for the communities and other actors involved in the co-creation process. In this paper, we study the barriers that inhibit the adoption of technologies to reach innovation levels and study comparative cases in rural areas of Cauca in Colombia. We develop and test a theory grounded framework, and we compile an overview of the most important of barriers.

Keywords: technology adoption, environmentally friendly technology, developing countries, rural production, innovation, appropriate technology

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Authors: K. Zehouani, I. Oldal

Abstract:

Purpose: In the human knee joint, degenerative joint disease may happen with time. The standard treatment of this disease is the total knee replacement through prosthesis implanting. The reason lies in the fact that this phenomenon causes different material abrasion as compare to pure sliding or rolling alone. This study focuses on developing a knee prosthesis geometry, which fulfills the mechanical and kinematical requirements. Method: The MSC ADAMS program is used to describe the rotation of the human knee joint as a function of flexion, and to investigate how the flexion and rotation movement changes between the condyles of a multi-body model of the knee prosthesis as a function of flexion angle (in the functional arc of the knee (20-120º)). Moreover, the multi-body model with identical boundary conditions is constituted, and the numerical simulations are carried out using the MSC ADAMS program system. Results: It is concluded that the use of the multi-body model reduces time and cost since it does not need to manufacture the tibia and the femur as it requires for the knee prosthesis of the test machine. Moreover, without measuring or by dispensing with a test machine for the knee prosthesis geometry, approximation of the results of our model to a human knee is carried out directly. Conclusion: The pattern obtained by the multi-body model provides an insight for future experimental tests related to the rotation and flexion of the knee joint concerning the actual average and friction load.

Keywords: biomechanics, knee joint, rotation, flexion, kinematics, MSC ADAMS

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Authors: Yeliz Mert Kantar, İsmail Yeni̇lmez, Ibrahim Arik

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In this study, the efficiency measurement of the top fifty Turkish Universities has been conducted. The top fifty Turkish Universities are listed by The Scientific and Technological Research Council of Turkey (TÜBITAK) according to the Entrepreneur and Innovative University Index every year. The index is calculated based on four components since 2018. Four components are scientific and technological research competency, intellectual property pool, cooperation and interaction, and economic and social contribution. The four components consist of twenty-three sub-components. The 2021 list announced in January 2022 is discussed in this study. Efficiency analysis have been carried out using the Stochastic Frontier Model. Statistical significance of the sub-components that make up the index with certain weights has been examined in terms of the efficiency measurement calculated through the Stochastic Frontier Model. The relationship between the efficiency ranking estimated based on the Stochastic Frontier Model and the Entrepreneur and Innovative University Index ranking is discussed in detail.

Keywords: efficiency, entrepreneur and innovative universities, turkish universities, stochastic frontier model, tübi̇tak

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Authors: B. S. Fatoyinbo, D. Stretch, O. T. Amoo, D. Allopi

Abstract:

This study extends the use of the Drainage Area Regionalization (DAR) method in generating synthetic data and calibrating PyTOPKAPI stream yield for an ungauged basin at a daily time scale. The generation of runoff in determining a river yield has been subjected to various topographic and spatial meteorological variables, which integers form the Catchment Characteristics Model (CCM). Many of the conventional CCM models adapted in Africa have been challenged with a paucity of adequate, relevance and accurate data to parameterize and validate the potential. The purpose of generating synthetic flow is to test a hydrological model, which will not suffer from the impact of very low flows or very high flows, thus allowing to check whether the model is structurally sound enough or not. The employed physically-based, watershed-scale hydrologic model (PyTOPKAPI) was parameterized with GIS-pre-processing parameters and remote sensing hydro-meteorological variables. The validation with mean annual runoff ratio proposes a decent graphical understanding between observed and the simulated discharge. The Nash-Sutcliffe efficiency and coefficient of determination (R²) values of 0.704 and 0.739 proves strong model efficiency. Given the current climate variability impact, water planner can now assert a tool for flow quantification and sustainable planning purposes.

Keywords: catchment characteristics model, GIS, synthetic data, ungauged basin

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

Abstract:

Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

Procedia PDF Downloads 261